docstr: Returns layer that embeds inputs, used for computing explanations.
  
  Captum adds an evaluation hook to this module returned by this function. The hook copies the module's return
  with .clone(). The module returned by this function must return a tensor, not a dictionary of tensors.
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code: def get_embedding_layer(self) -> nn.Module:
      """Returns layer that embeds inputs, used for computing explanations.
  
      Captum adds an evaluation hook to this module returned by this function. The hook copies the module's return
      with .clone(). The module returned by this function must return a tensor, not a dictionary of tensors.
      """
      return next(self.children())
  
file_path: ludwig/ludwig/encoders/base.py
imports: from abc import ABC, abstractmethod
  from torch import nn
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.utils.torch_utils import LudwigModule
label_desc: Use image node_id 2 for calling the Encoder obj's underlying member method code with example usage: obj.get_embedding_layer() and returns: next